Hi Michael,
On Wed, Oct 14, 2015 at 7:06 PM, Michael Reutlinger <rd...@mulchi.de> wrote:
>
> I observed a memory leak while using the RDKit to calculate descriptors
> for a large library of compounds.
>
> I tracked it down to the Ipc descriptor and it is reproducible with this
> small script:
>
> from rdkit.ML.Descriptors import MoleculeDescriptors
> from rdkit import Chem
>
> calculator = MoleculeDescriptors.MolecularDescriptorCalculator(['Ipc'])
> for n in range(100000):
> mol = Chem.MolFromSmiles('CC(C)Cc1ccc(cc1)C(C)C(=O)O')
> x = calculator.CalcDescriptors(mol)
> if not n % 100: print n
>
> I tested it on my Linux workstation (Redhat 6). The process memory
> consumption increases to several hundred mb. Interestingly, I can't
> reproduce it on my Mac running the latest os.
>
I can't reproduce it on my Mac either. I'm on vacation and don't have
access to my linux box, but I will see if I can reproduce it when I'm back
next week. Which version(s) of python are you using on the machines?
My guess is that the leak is caused by getDistanceMatrix in MolOps.cpp.
> Specifically, a missing delete for the distMat pointer (in the getDistanceMat
> documentation is a note that the pointer should be deleted by the caller).
> However, I am not a c++ programmer myself and this analysis might not be
> the true cause.
>
The docs actually say that the pointer should *not* be deleted by the
caller, but that's not relevant here anyway. The C++ object is copied into
a new python numpy array object before being returned to the user.
> I hope it is reproducible on other systems and easy to fix :-) If you need
> additional information please let me know.
>
The simplest possible test would be to see if you get the same leak when
you just call Chem.GetDistanceMatrix(mol,0) repeatedly.
Best,
-greg
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